{"id":"W4289276764","doi":"10.48550/arxiv.1811.09851","title":"An adaptive treatment recommendation and outcome prediction model for\\n metastatic melanoma","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Melanoma; Cluster analysis; Cancer; Computer science; Observational study; Medicine; Cluster (spacecraft); Skin cancer; Cohort; Cancer registry; Metastatic melanoma; Oncology; Data mining; Artificial intelligence; Internal medicine; Cancer research","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008847635,0.0006217373,0.0009491199,0.0008177999,0.000398915,0.0005905823,0.001286611,0.00114624,0.00287327],"category_scores_gemma":[0.001945821,0.0003289999,0.0006119332,0.0005329443,0.0001746521,0.0004012509,0.0003551514,0.001151628,0.0006642577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000950883,"about_ca_system_score_gemma":0.001158665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04318348,"about_ca_topic_score_gemma":0.04314456,"domain_scores_codex":[0.9996905,0.00005734282,0.00002563808,0.0001260961,0.00004562073,0.0000547479],"domain_scores_gemma":[0.999055,0.0005163599,0.00008655273,0.00003840443,0.0002399231,0.00006367504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009935473,0.0009729246,0.04426794,0.0001404273,0.000243664,0.0005190215,0.000117075,0.6684299,0.002859775,0.00144604,0.01723514,0.2627746],"study_design_scores_gemma":[0.00001819531,0.0000284645,0.001279417,0.000003935001,0.00001723924,0.00001977223,0.000006312472,0.9979987,0.0001819187,0.0002431499,0.0001983194,0.000004619792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5497463,0.002559612,0.4217599,0.006954486,0.0005756497,0.0004686139,0.00652337,0.004588976,0.006822979],"genre_scores_gemma":[0.9496028,0.0003204432,0.04146817,0.0005342457,0.0001834461,0.000252547,0.002711461,0.00003898287,0.004887912],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04318348,"threshold_uncertainty_score":0.08586425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1542483622611175,"score_gpt":0.2520485732642576,"score_spread":0.09780021100314007,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}